Python – basicsHome Training Catalog Python – basics Analysis Data Science Open Source Short courses On-site courses Remote/Virtual Face-to-face English French Objectives Understand how data is represented, know how to manipulate simple data structures, master the basics of the numpy and scipy libraries for numerical computation and basic statistical functions, learn the basics of graphical visualization with matplotlib. At the end of this training, the participant should be able to write simple analysis scripts working either with artificial data or with data sources that do not require major pre-processing. He/she will know how to implement the main statistical tests for the comparison of two samples and perform basic exploratory graphs. Prerequisites: None Pedagogical and technical material and resources: Sessions with the trainer, training material in digital format, balance between theoretical and practice, concrete cases. Assessment: Practical application and exercises Results & skills expected at the end of the training: At the end of this training, the participant should be able to write simple analysis scripts working either with artificial data or with data sources that do not require major pre-processing. He will be able to implement the main statistical tests for the comparison of two samples and perform basic exploratory graphs. Program Day 1 The working environment: Python 2 and 3.x The presentation of the different consoles and debugging in Python: Anaconda Jupyter Spyder Data types: lists, dictionaries Control structures The functions, methods and packages DAY 2 Data handling and cleaning: numpy: Basic objects and manipulation of 2-dimensional arrays (array and numeric calculation functions, random number generators) scipy: Basic functionality (scientific functions and basic statistical tests) The probability distributions and univariate statistics. matplotlib: basic features: scatterplot, box plot, histogram Simple scripting Download the full program Duration 14 hours Level Beginner Audience Anyone wishing to discover the basic Python tools. Participants 8 people maximum Please contact us for a personnalized offer. Are you looking for information about a training course? You want to set up a customized training session? Contact our pedagogical team! Notice: JavaScript is required for this content. Upcoming trainings Intelligence Artificielle Générative Integrating Artificial Intelligence into your scientific teams Objectives Understand Generative AI, its functioning, and its limitations Explore the applications of Generative AI and use cases for scientists Define a plan for integrating Generative AI into your team/laboratory and prioritize the first actions 13 May Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Introduction to R for Basic Statistical Analysis with the Help of Generative AI (Beginner) Objectives Discover the fundamentals of R and generative AI tools. Learn the basics of descriptive statistical analysis and apply them to real-world datasets. Learn how to automate common tasks in R using generative AI. Master the creation of simple visualizations and data presentation. Get introduced to the concepts of simple regressions and hypothesis testing. Generate workflows and automated reports with R Markdown. 19, 20, 22 and 23 May Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Generative Artificial Intelligence for Scientific Monitoring Objectives Describe the general working principle of Deep Learning and Generative Artificial Intelligence. Use advanced prompting techniques to meet business needs. Synthesize articles and scientific content by producing concise summaries that highlight key points and main conclusions. Improve technological monitoring by configuring, customizing, and automating generative artificial intelligence tools to monitor and summarize the latest research published in specific fields. Identify key points in a specific scientific field and detect missing research topics needed to complete an existing theoretical model. Translate articles. 19 and 23 May Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Generative AI for Qualitative Analysis Objectives Understand the fundamentals of generative AI and its applications. Master AI-assisted qualitative analysis techniques. Use AI for analyzing and presenting qualitative data. 02 and 03 June Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Artificial Intelligence for Scientific Communication and Popularization Objectives Understand the fundamentals of Generative AI and its applications in communication Use AI in communication strategy: defining target audiences, structuring messages, choosing formats… 03 and 04 June Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Enhance your statistical analyses with R and Generative AI (Advanced) Objectives • Deepen your mastery of R to perform advanced statistical analyses.• Discover and leverage generative AI tools to automate common tasks in data analysis.• Optimize analytical processes by integrating automated workflows.• Structure complex workflows effectively and innovatively.• Strengthen the understanding and application of advanced statistical concepts to real and simulated cases. 09, 10, 12 and 13 June Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Prompt Engineering Objectives Describe how a Generative AI (GenAI) works in order to optimize its use in daily tasks Apply prompt engineering methods to use GenAI tools effectively Identify use cases within your professional environment 19 June Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Generative Artificial Intelligence for Research Education Objectives Discover the general principles of Deep Learning and Generative Artificial Intelligence, and benefit from the potential of Generative AI tools. Use advanced prompting techniques to meet business needs. Classify generative AI tools according to the media they implement (text-to-text, text-to-image, etc.), and select the right tool for a specific use case. Produce educational activities such as course notes, study guides, or chapter summaries to assist students in their learning. Design exams and quizzes based on the training content developed for students, saving time in course preparation. Generate scenarios or case studies for group projects, based on current topics or scientific advancements, to expand the possibilities of course facilitation (content, group workshops, etc.). Adapt your teaching and prepare your students for the Generative AI revolution. 26 June03 July Register Ask for a quote Previous Next
